Algorithm Research & Explore
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1069-1072,1080

Traffic detection algorithm for identify overlapping noise

Ma Qinglu
Zou Zheng
School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China

Abstract

Traditionally, the short-term energy method or the short-term average magnitude method is not able to identify the overlapping traffic noise segments effectively. In order to solve the problem, this paper proposed a traffic detection algorithm based on the SV features. First, it filtered and denoised the traffic noise which contained overlapping noise. Next, it extracted the SV features of the traffic noise via FFT, and then smoothed the SV features. Finally, based on the SV features and the principle of dual-thresholds judgment, it detected the endpoints of the traffic noise and identified the overlapping noise. In condition of a single lane and low traffic, experiments on dataset of traffic noise demonstrate that the accuracy outperforms other usual methods by 20%.

Foundation Support

中国博士后科学基金面上资助项目(2016M592645)
重庆市社会科学规划重大资助项目(2018ZD18)
重庆市人力资源和社会保障局博士后科研基金资助项目(XM2015057)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.08.0746
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 4
Section: Algorithm Research & Explore
Pages: 1069-1072,1080
Serial Number: 1001-3695(2020)04-022-1069-04

Publish History

[2020-04-05] Printed Article

Cite This Article

马庆禄, 邹政. 一种识别重叠噪声的交通量检测算法 [J]. 计算机应用研究, 2020, 37 (4): 1069-1072,1080. (Ma Qinglu, Zou Zheng. Traffic detection algorithm for identify overlapping noise [J]. Application Research of Computers, 2020, 37 (4): 1069-1072,1080. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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